Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Indonesian Journal of Computer Science and Engineering
Afriani, Annisa
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Segmentation of Problematic Loan Customers Using The K-Means Clustering Algorithm to Support Strategic Decision-Making (Case Study: Bank Mega Finance Bengkulu) Novrian, Willi; Afriani, Annisa; Sari, Julia Purnama; Putra, Yusran Panca
Indonesian Journal of Computer Science and Engineering Vol. 2 No. 01 (2025): IJCSE Volume 02 Number 02, November 2025
Publisher : CV. Cendekiawan Muda Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study analyzes 5,305 records of non-performing loan customers from Bank Mega Finance Bengkulu using the K-Means Clustering algorithm within the CRISP-DM framework. Based on variables such as tenure, outstanding balance, installment amount, and payment delay duration, the analysis identified three customer risk clusters (high, medium, and low) with a Davies-Bouldin Index (DBI) of 0.201, indicating good clustering quality. The segmentation results can help determine collection priorities, loan restructuring, and risk mitigation strategies, demonstrating the effectiveness of data mining in supporting strategic decision-making in banking risk management.
Co-Authors Julia Purnama Sari Novrian, Willi Putra, Yusran Panca